Search Results (60)

Background: High-frequency ultrasound (HFUS) has emerged as a valuable non-invasive imaging modality for the preoperative assessment of basal cell carcinoma (BCC). However, its ability to reliably differentiate between histopathological subtypes based on morphological and vascular characteristics requires further validation. Methods: Between January 2010 and December 2011, 320 patients with a total of 330 histologically confirmed BCC lesions were examined using HFUS (15–18 MHz linear transducer). Lesions were classified according to ultrasound contour (sharp vs. irregular) and vascularity (hypervascular vs. hypovascular) and correlated with histopathological subtype (solid vs. infiltrative). Postoperative ultrasound follow-up was performed in a subset of patients for recurrence detection. Results: Solid BCCs were predominantly characterised by sharp, well-defined margins, whereas infiltrative tumours more frequently exhibited irregular contours. This association was highly significant (χ² = 24.7, df = 1, p < 0.001; OR = 71.9, 95% CI: 37.0–139.8). Vascularity patterns also differed significantly between subtypes: solid tumours were more likely to present with hypervascular features, while infiltrative tumours more frequently exhibited hypovascular patterns (χ² = 23.8, df = 1, p < 0.001; OR = 3.24). No statistically significant associations were observed between ultrasound morphology and patient sex or age. Among patients who participated in postoperative HFUS follow-up, seven histologically confirmed recurrences were detected. Conclusions: HFUS provides reliable preoperative information on BCC morphology and vascularity, enabling accurate differentiation between solid and infiltrative subtypes. These findings support the role of HFUS as a valuable adjunct to dermatoscopy in treatment planning and postoperative surveillance of BCC. Full article

Psoriasis vulgaris is a polygenic, immunomediated dermatological condition, characterized pathophysiologically by abnormal proliferation of the epidermis and immune response disorders, evidenced by the presence of a dermal inflammatory infiltrate accompanied by exocytosis. The prevalence of this disease is continuously increasing, and the significant impact on quality of life is determined by both the severity of the skin manifestations and the associated comorbidities, which underlines the importance of early diagnosis. Among the imaging methods useful in the diagnosis and monitoring of psoriasis vulgaris are dermatoscopy and high-frequency cutaneous ultrasonography (HFUS). Dermatoscopy is a valuable complementary imaging tool in assessing the therapeutic response in patients with psoriasis vulgaris. Although clinical lesions may show partial or complete remission, the persistence of the specific vascular architecture—characterized by dilated and branched capillaries—suggests the maintenance of disease activity and justifies the need for continued treatment. HFUS allows the identification of characteristic changes in psoriatic plaques, such as homogeneous thickening of the epidermis, visible as a hyperechoic band, the presence of a hypoechoic subepidermal band, and thickening of the dermis. Evaluation with 20 MHz probes can significantly contribute to monitoring therapeutic efficacy, since the first observable changes under topical and/or systemic treatment include a reduction in the thickness of the epidermis, dermis, and hypoechoic subepidermal band. The integration of dermatoscopy and HFUS within the clinical evaluation allows for a complex and precise approach to the management of patients with psoriasis vulgaris, facilitating objective monitoring of disease progression and appropriate adjustment of therapy. Full article

Background and Objectives: Dermoscopy is a non-invasive clinical tool that allows for the in vivo visualization of pigmented and non-pigmented structures in the epidermis and the papillary dermis. The standard handheld dermoscopy offers a magnification of 10×, whereas the videodermatoscopes can obtain a magnification of up to 140×. Recently, a new method called magnified dermoscopy was introduced, in which a magnification of 400× can be achieved. Materials and Methods: This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. Comprehensive research was conducted using the PubMed database on 9 June 2025, using the following keywords: “high magnification” or “super high magnification” or “optical super high magnification” or “400×”, and “dermoscopy” or “dermatoscopy”. Results: From a total of 237 records retrieved, 25 were found to be suitable for this review, and consisted of: four prospective studies, three retrospective studies, six case series, ten case reports and two image letters. Conclusions: This review summarizes the current knowledge on magnified dermoscopy, compiling existing data and exploring future perspectives for this emerging non-invasive diagnostic method. Full article

Dermoscopy is an essential, non-invasive diagnostic tool that has transformed the evaluation of pigmented skin lesions and is nowadays also increasingly recognized for its utility in general dermatology. Originally developed for the early detection of melanoma, dermoscopy now aids in diagnosing a wide range of non-neoplastic skin disorders—including inflammatory, infectious, and infiltrative conditions—by revealing morphological features invisible to the naked eye. Among these, facial dermatoses represent a diagnostically challenging group of disorders with overlapping clinical presentations. This review provides a comprehensive overview of the latest literature on dermoscopy in general dermatology, with a specific focus on facial dermatoses. Relevant information for this article was obtained through a comprehensive PubMed search using disease names along with the terms ‘dermoscopy’ and ‘dermatoscopy’. Despite its growing relevance, this field remains underexplored, largely due to the lack of standardized dermoscopic criteria and inconsistent terminology, which pose challenges to broader clinical implementation. Nonetheless, current evidence highlights the promising role played by dermoscopy as an adjunctive diagnostic method, particularly when used by experienced clinicians in combination with detailed patient history and clinical examination. Dermoscopy of facial dermatoses has the potential to significantly improve diagnostic precision in everyday practice. With continued research, greater standardization, and wider clinician training, dermoscopy is well-positioned to become as integral to the diagnosis of inflammatory and infectious dermatoses as it is to skin cancer detection. Full article

Background: Skin cancer represents one of the most prevalent malignancies worldwide, with melanoma accounting for approximately 75% of skin cancer-related deaths despite comprising fewer than 5% of cases. Early detection dramatically improves survival rates from 14% to over 99%, highlighting the urgent need for accurate and accessible diagnostic tools. While deep learning has shown promise in dermatological diagnosis, existing approaches lack clinical explainability and deployable interfaces that bridge the gap between research innovation and practical healthcare applications. Methods: This study implemented a comprehensive multimodal deep learning framework using the HAM10000 dataset (10,015 dermatoscopic images across seven diagnostic categories). Three CNN architectures (DenseNet-121, EfficientNet-B3, ResNet-50) were systematically compared, integrating patient metadata, including age, sex, and anatomical location, with dermatoscopic image analysis. The first implementation of XRAI (eXplanation with Region-based Attribution for Images) explainability for skin lesion classification was developed, providing spatially coherent explanations aligned with clinical reasoning patterns. A deployable web-based clinical interface was created, featuring real-time inference, comprehensive safety protocols, risk stratification, and evidence-based cosmetic recommendations for benign conditions. Results: EfficientNet-B3 achieved superior performance with 89.09% test accuracy and 90.08% validation accuracy, significantly outperforming DenseNet-121 (82.83%) and ResNet-50 (78.78%). Test-time augmentation improved performance by 1.00 percentage point to 90.09%. The model demonstrated excellent performance for critical malignant conditions: melanoma (81.6% confidence), basal cell carcinoma (82.1% confidence), and actinic keratoses (88% confidence). XRAI analysis revealed clinically meaningful attention patterns focusing on irregular pigmentation for melanoma, ulcerated borders for basal cell carcinoma, and surface irregularities for precancerous lesions. Error analysis showed that misclassifications occurred primarily in visually ambiguous cases with high correlation (0.855–0.968) between model attention and ideal features. The web application successfully validated real-time diagnostic capabilities with appropriate emergency protocols for malignant conditions and comprehensive cosmetic guidance for benign lesions. Conclusions: This research successfully developed the first clinically deployable skin lesion classification system combining diagnostic accuracy with explainable AI and practical patient guidance. The integration of XRAI explainability provides essential transparency for clinical acceptance, while the web-based deployment democratizes access to advanced dermatological AI capabilities. Comprehensive validation establishes readiness for controlled clinical trials and potential integration into healthcare workflows, particularly benefiting underserved regions with limited specialist availability. This work bridges the critical gap between research-grade AI models and practical clinical utility, establishing a foundation for responsible AI integration in dermatological practice. Full article

Early detection of cancer is critical for effective treatment, particularly for aggressive malignancies like skin cancer and brain tumors. This research presents an integrated deep learning approach combining augmentation, segmentation, and classification techniques to identify diverse tumor types in skin lesions and brain MRI scans. Our method employs a fine-tuned InceptionV3 convolutional neural network trained on a multi-modal dataset comprising dermatoscopy images from the Human Against Machine archive and brain MRI scans from the ISIC 2023 repository. To address class imbalance, we implement advanced preprocessing and Generative Adversarial Network (GAN)-based augmentation. The model achieves 97% accuracy in classifying images across ten categories: seven skin cancer types, multiple brain tumor variants, and an “undefined” class. These results suggest clinical applicability for multi-cancer detection. Full article

Background: Ultrasound and colour Doppler are adjuvant techniques widely used in clinical settings in obstetrics, cardiology, and others. Its use in dermatology is more incipient although it presents potential for clinical use namely in dermo-oncology. Objective: This study explores the usefulness of the combination of cutaneous ultrasound with Doppler after digital dermatoscopy in distinguishing between most common benign and malignant skin lesions, focusing on the importance of different vascular patterns. To streamline the diagnostic process, we propose a combined imaging workflow that integrates dermoscopic findings with vascular and structural data obtained via Doppler ultrasound. Methods: In total, 42 benign and malignant skin tumours were analysed in a population of 42 patients using a Fotofinder digital dermatoscopy device and a GE ultrasound machine with a high-frequency probe (20 MHz). Doppler was applied to assess lesion vascularization and identify distinct blood flow patterns. Results: Cutaneous ultrasound revealed that malignant lesions often exhibited intense and disorganized vascularization, while benign lesions displayed more ordered and peripheral blood flow patterns. In all of our cases, ultrasound with Doppler imaging clarified the uncertainties raised by dermatoscopy. Conclusions: The use of Doppler cutaneous ultrasound after digital dermatoscopy proved to be a valuable tool to aid the diagnosis in dermatology, as it improved the differential diagnosis between benign and malignant lesions, contributing to the establishment of the final diagnosis in the studied cases. Full article

Teledermatology relies on digital transfer of dermatological images, but compression and resolution differences compromise diagnostic quality. Image enhancement techniques are crucial to compensate for these differences and improve quality for both clinical assessment and AI-based analysis. We developed a customized image degradation pipeline simulating common artifacts in dermatological images, including blur, noise, downsampling, and compression. This synthetic degradation approach enabled effective training of DermaSR-GAN, a super-resolution generative adversarial network tailored for dermoscopic images. The model was trained on 30,000 high-quality ISIC images and evaluated on three independent datasets (ISIC Test, Novara Dermoscopic, PH²) using structural similarity and no-reference quality metrics. DermaSR-GAN achieved statistically significant improvements in quality scores across all datasets, with up to 23% enhancement in perceptual quality metrics (MANIQA). The model preserved diagnostic details while doubling resolution and surpassed existing approaches, including traditional interpolation methods and state-of-the-art deep learning techniques. Integration with downstream classification systems demonstrated up to 14.6% improvement in class-specific accuracy for keratosis-like lesions compared to original images. Synthetic degradation represents a promising approach for training effective super-resolution models in medical imaging, with significant potential for enhancing teledermatology applications and computer-aided diagnosis systems. Full article

The use of artificial intelligence (AI) in dermatology is skyrocketing, but a comprehensive overview integrating regulatory, ethical, validation, and clinical issues is lacking. This work aims to review current research, map applicable legal regulations, identify ethical challenges and methods of verifying AI models in dermatology, assess publication trends, compare the most popular neural network architectures and datasets, and identify good practices in creating AI-based applications for dermatological use. A systematic literature review is conducted in accordance with the PRISMA guidelines, utilising Google Scholar, PubMed, Scopus, and Web of Science and employing bibliometric analysis. Since 2016, there has been exponential growth in deep learning research in dermatology, revealing gaps in EU and US regulations and significant differences in model performance across different datasets. The decision-making process in clinical dermatology is analysed, focusing on how AI is augmenting skin imaging techniques such as dermatoscopy and histology. Further demonstration is provided regarding how AI is a valuable tool that supports dermatologists by automatically analysing skin images, enabling faster diagnosis and the more accurate identification of skin lesions. These advances enhance the precision and efficiency of dermatological care, showcasing the potential of AI to revolutionise the speed of diagnosis in modern dermatology, sparking excitement and curiosity. Then, we discuss the regulatory framework for AI in medicine, as well as the ethical issues that may arise. Additionally, this article addresses the critical challenge of ensuring the safety and trustworthiness of AI in dermatology, presenting classic examples of safety issues that can arise during its implementation. The review provides recommendations for regulatory harmonisation, the standardisation of validation metrics, and further research on data explainability and representativeness, which can accelerate the safe implementation of AI in dermatological practice. Full article

The type of non-professional or professional support received affects the quality of life of the patient and their caregivers. Social support is the type of interaction that is taken by the patient and his caregivers in a problematic, difficult, stressful, or critical situation. Aim: The aim of the study was to assess the impact of social support on the functioning of patients under nursing home care. Material and methods: The study included 148 chronically ill patients under home nursing care. The study used the diagnostic survey method; the research technique was a questionnaire containing basic data about the respondent and the Social Support Scale (SWS) by Krystyna Kmiecik-Baran. Results: The need to continue the causal treatment at home means that the main source of support for care beneficiaries are nurses who provide medical services at the patient’s home, supported by doctors and family members of the patient. According to patients’ subjective assessment of the support they received from nurses, patients rated the informational support provided by nurses highest at 14.3 points and emotional support at 13.3 points (SD 1.776). on a scale where the maximum score was 16 points. In the opinion of the surveyed patients, the value-added support provided was the lowest-rated category by patients, 9.74 points (SD 2.505). Instrumental support was also rated very poorly by the respondents (10.17 points (SD 2.069). In each category, there was no statistically significant difference at the p < 0.05 level in the respondents’ evaluation, which means that the expressed opinion on each type of support from the highest to the lowest evaluation: informational, emotional, instrumental, and evaluative—overlapped in the patient group and the family group. Conclusions: Patients under home care highly appreciated the support provided to them by the nursing staff. Social support for a chronically ill person who requires constant care and care by the nursing staff is a form of direct impact that relieves stress and tension, minimizes the effects of the disease, directly affects the course of treatment and care, and prevents stigmatization. Full article

Background/Objectives: Skin cancer is increasingly prevalent. Non-melanoma skin cancers pose a challenge, as most lesions are diagnosed at later stages and often lead to complications. Although dermatoscopy has emerged as a valuable tool that enhances the confidence of dermatologists, specific patterns for accurately identifying various subtypes of non-melanoma skin cancer have yet to be detailed. This study aimed to investigate dermatoscopic clues that facilitate accurate diagnosis of non-melanoma skin cancer among Mexican individuals. There is insufficient acknowledgment of high skin cancer rates among non-Whites. Methods: The study included fifty-three patients diagnosed with non-melanoma skin cancer, aged 39 to 89, who visited an academic dermatology department for skin examinations. Two certified dermatologists evaluated at least three dermatoscopy images for each lesion. A biopsy was taken to confirm the preliminary diagnosis. Statistical analysis was performed using GraphPad Prism v8.0, considering a probability (p) value of less than 0.05 as significant. Results: Most patients were classified as phototype III. Patients with phototype IV were younger at the time of diagnosis. Basal cell carcinomas were the most common cancer subtype. Nodular and ulcerated tumors were the most prevalent morphology. The dermatoscopic examination revealed that 60% of the lesions were pigmented, with a predominance of polymorphic vascular patterns. Squamous cell carcinomas exhibited monomorphic vascular structures. Both groups’ blood vessel arrangements and specific patterns were primarily radial. Conclusions: Phototypes III and IV are predominant in the Mexican population; however, patients with non-melanoma skin cancer tend to be under 60 years of age at diagnosis. Although prominent reticular lines were distinctive of the ulcerated lesions, finding any pathognomonic pigmentary feature for non-melanoma skin cancer subtypes or locations was impossible. A polymorphic pattern of blood vessels, with a predominance of linear vessels, typically indicates the presence of Basal cell carcinoma. In contrast, a monomorphic pattern with a predominance of comma vessels is more suggestive of Squamous cell carcinoma. Full article

Background/Objectives: Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer, with diverse clinical presentations. This study aims to correlate findings from dermoscopy, ultrasonography, ex vivo confocal microscopy, and histology to improve diagnostic accuracy and guide better clinical management of cSCC. Methods: This cross-sectional study, conducted between July 2022 and December 2024, included 26 patients with 35 clinically suspicious cSCC tumors, analyzed through clinical, dermoscopic, high-frequency ultrasound (HFUS), ex vivo confocal fluorescence microscopy (FCM), and histopathology. Tumors were evaluated for various clinical, imaging, and histopathological criteria, such as tumor thickness, vascularization, differentiation degree, and invasion level, with FCM applied to 24 tumors for advanced microscopic analysis. Results: The study analyzed 35 cases of histopathologically confirmed cSCC, finding that invasive SCC was associated with greater tumor thickness, increased vascularization, and ulceration on both ultrasound and dermatoscopy, while in situ SCC showed homogeneous echogenicity and specific dermoscopic patterns like dotted vessels and white halos. Strong correlations were identified between ultrasound and histopathological measurements of tumor thickness and invasion depth, and confocal microscopy revealed that features like plump bright cells and nest-like structures were linked to invasive and poorly differentiated tumors. Conclusions: This study uniquely integrates advanced imaging techniques—dermatoscopy, skin ultrasound, and ex vivo confocal microscopy—with histopathological analysis to provide new insights into tumor grade, vascularity, and invasion depth in cSCC, enhancing non-invasive diagnosis. Full article

Introduction: Basal cell carcinoma (BCC) is the most frequently diagnosed skin cancer globally. Despite the well-established dermoscopic features of BCC, overlapping characteristics with other benign and malignant skin conditions cause challenges in differential diagnosis. Part III of this review highlights the role of dermoscopy in differential diagnosis, treatment planning, therapy monitoring and the integration of novel technologies including ultraviolet-induced fluorescence dermoscopy (UVFD) and optical super-high magnification dermoscopy (OSHMD). Methods: A search of the PubMed database was conducted for studies reporting on advances in the dermoscopic assessment of BCC, including differential diagnosis, treatment, monitoring and novel diagnostic technologies. Results: Even entities with well-defined dermoscopic features distinguishing them from BCC can sometimes mimic BCC. Additionally, rare lesions such as neurothekeoma, reticulohistiocytoma, solitary circumscribed neuroma, dermal leiomyosarcoma and various adnexal tumors often remain dermoscopically indistinguishable from BCC, which underscores the importance of histopathology as the diagnostic gold standard. Dermoscopy aids in delineating the tumor margins, optimizing Mohs micrographic surgery (MMS) and traditional excision. It may also help to monitor therapeutic effects by detecting the disappearance of BCC patterns, the presence of residual tumor or recurrences. Dermoscopy may aid in the prediction of therapeutic responses to imiquimod, photodynamic therapy or vismodegib. UVFD and OSHMD appear to be valuable complementary diagnostic techniques for detecting BCC. UVFD seems to be particularly valuable for the detection of small tumors (<5 mm), facial lesions and nodular or non-pigmented BCC subtypes, while OSHMD is useful for the assessment of superficial and non-pigmented BCCs. Three-dimensional total-body photography enhances diagnostic precision but, so far, only when used in combination with traditional dermoscopy. Conclusions: Dermoscopy is valuable for margin delineation, therapy monitoring and differential diagnosis but can be inconclusive, which highlights the role of histopathology as the gold standard. Modifications in dermoscopy technique may further enhance its accuracy. Full article

Introduction: Basal cell carcinoma (BCC) is the most common malignant skin tumor. While rarely fatal, it can cause local tissue damage. Part I of the review summarizes the dermoscopic features of BCC and the diagnostic accuracy of dermoscopy in the diagnosis of BCC. Methods: A search of the PubMed database was performed for studies reporting on the diagnostic accuracy of dermoscopy or dermoscopic findings in BCC, either pigmented or non-pigmented, located anywhere on the body, of any histopathologic subtype, size and at any age of onset. Results: BCC was found to present with a wide range of dermoscopic features, including white structures (shiny white lines, shiny white areas, rosettes), yellow structures (milia-like cysts, yellow lobular-like structures), multiple aggregated yellow-white globules (MAY globules), blue structures (blue ovoid nests), vascular structures (arborizing vessels, short fine telangiectasias), multiple small erosions/ulcerations, features of regression (pepper-like structures, white scar-like areas) and pigmented structures (spoke-wheel areas, maple leaf-like areas (MLLAs), blue/gray dots). Dermoscopy showed a sensitivity of 67.6–98.6% and a positive predictive value (PPV) of 85.9–97% in identifying BCC. The physician’s experience and training improve the accuracy, however, BCCs on the trunk and extremities, particularly of superficial subtypes, may still constitute a challenge. Conclusions: Dermoscopy, especially when performed by a trained physician, increases the accuracy of early BCC detection. Full article

The diagnosis, interpretation, and classification of melanocytic tumors is a very complex topic in the pathology and dermatopathology field that lacks standardization and is still subject to discordance and debate. Here, we review the definitions of dysplastic nevus and superficial atypical melanocytic proliferations and provide an overview of some areas still subject to debate and some attempts of standardization. Furthermore, we describe an algorithmic classification, and provide some examples of clinico-pathological correlation. This step-by-step algorithm has an educational purpose and may automatize the work of dermatopathologists. We hope that through further molecular studies, this fine-grained scheme will prove to be related to the biological behavior of these atypical melanocytic lesions. Full article